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Crowdsourcing: A Definition

I like to use two definitions for crowdsourcing:

The White Paper Version: Crowdsourcing is the act of taking a job traditionally performed by a designated agent (usually an employee) and outsourcing it to an undefined, generally large group of people in the form of an open call.

The Soundbyte Version: The application of Open Source principles to fields outside of software.

The Rise of Crowdsourcing

Read the original article about crowdsourcing, published in the June, 2006 issue of Wired Magazine.

May 16, 2008

Chapter 7-What the Crowd Knows: Collective Intelligence in Action

Whereas Chapter 6 explored the theory of collective intelligence, Chapter 7 looks at how collective intelligence is being employed in real-life crowdsourcing examples.

In the late fall of 2004 Karim Lakhani, a PhD candidate at MIT’s Sloan School of Management, was suffering from a common affliction among graduate students. “I hit that point where I just couldn’t stand to spend any more time on my own dissertation,” recalls Lakhani. He’d been analyzing how innovations emerge in open source software, but after four years of work, he was burnt out. It was time for an extended vacation. “I stopped everything and read Neal Stephenson’s Baroque Cycle.” Stephenson’s trilogy is a work of historical fiction about the Age of Enlightenment in Europe, and it made a big impact on Lakhani. “It’s all about the establishment of the Royal Society and the dawn of rational thinking about the world and the invention of calculus.” By Lakhani’s lights, the Baroque Cycle was a narrative history of innovation.

One passage in particular caught Lakhani’s attention. Stephenson related the true story of the longitude prize. In 1714 the British established a commission offering 20,000 pounds (roughly $6 million today) to anyone who could solve the mystery of longitude. The Royal Navy’s inability to measure lateral progress across the oceans had resulted in the loss of untold numbers of ships and their cargoes, causing a serious drain on government finances. “The top scientific minds of that time, including Isaac Newton, had tried to find a device that could determine longitude, and none succeeded,” notes Lakhani. The solution—a clock that operated with superb accuracy, even during the rigors of an overseas voyage—was developed by John Harrison, an uneducated cabinetmaker from Yorkshire. “I read that and thought, ‘Huh. Kind of like open source. Someone poses a problem and all sorts of random, strange people show up and say I’ve got an answer for you, and it’s never the one you’d anticipate.” The longitude prize constitutes the earliest known example of crowdcasting—broadcasting a problem to the widest possible audience in the blind hope that someone, somewhere—maybe even a Yorkshire cabinetmaker—will come up with a solution.

Lakhani returned to his dissertation, but now he was determined to look
at innovation with a much broader view. He’d heard of the
problem-solving scientists at InnoCentive, and wondered whether the
company wasn’t a modern-day version of the Longitude Prize. “I told
them I wanted to figure out how their problems were solved. They were
thrilled.” Lakhani teamed up with a PhD candidate at the Copenhagen
Business School and two InnoCentive scientists. Over the course of the
next year, they looked at 166 scientific problems afflicting the
R&D labs at 26 separate firms. In the summer of 2007 they published
their findings as a Harvard Business School working paper . The results
ran counter to decades of conventional wisdom in the sciences, but they
probably wouldn’t have surprised John Harrison.

A Whole New Paradigm

The future of corporate R&D can be found above Kelly’s Auto Body on
Shanty Bay Road in Barrie, Ontario. This is where Ed Melcarek, 59,
keeps his “weekend crash pad,” a one-bedroom apartment littered with
amplifiers, a guitar, electrical transducers, two desktop computers, a
trumpet, half of a pontoon boat, and enough electric gizmos to stock a
RadioShack. On most Saturdays, Melcarek comes in, pours himself a St.
Remy, lights a Player cigarette, and attacks problems that have stumped
some of the best corporate scientists at Fortune 500 companies.

Not everyone in the crowd wants to make T-shirts. Some have the kind of
scientific talent and expertise that used to exist only in rarefied
academic environments. In the process, forward-thinking companies are
changing the face of R&D. Exit the white lab coats; enter Melcarek,
who like the chemist Giorgia Sgargetta, is one of the 140,000 “solvers”
who make up the network of scientists on InnoCentive. Previously I
looked at InnoCentive’s ability to harness the excess capacity of
people like Melcarek and Sgargetta. Now it’s time to take a deeper look
at InnoCentive’s methodology, as it illustrates the ideas laid out in
the previous chapter.

Pharmaceutical maker Eli Lilly funded InnoCentive’s launch in 2001 as a
way to connect with brainpower outside the company – people who could
help develop drugs and speed them to market. From the outset,
InnoCentive threw open the doors to other firms eager to access the
network’s trove of ad hoc experts. Companies like Boeing, DuPont, and
of course, Procter & Gamble now post their most ornery scientific
problems on InnoCentive’s Website; anyone on InnoCentive’s network can
take a shot at cracking them. The companies generally pay solvers
anywhere from $10,000 to $100,000 per solution. (They also pay
InnoCentive a fee to participate.) Jill Panetta, InnoCentive’s chief
scientific officer, says more than 30 percent of the problems posted on
the site have been cracked, “which is 30 percent more than would have
been solved using a traditional, in-house approach.”

“Everyone I talk to is facing a similar issue in regards to R&D,”
says Larry Huston, Procter & Gamble’s former vice president of
innovation and knowledge. “Every year research budgets increase at a
faster rate than sales. The current R&D model is broken.” P&G
is one of InnoCentive’s earliest and best customers, but the company
works with other crowdsourcing networks as well. YourEncore, for
example, allows companies to find and hire retired scientists for
one-off assignments. NineSigma is an online marketplace for
innovations, matching seeker companies with solvers in a marketplace
similar to InnoCentive. “People mistake this for outsourcing, which it
most definitely is not,” Huston says. “Outsourcing is when I hire
someone to perform a service and they do it and that’s the end of the
relationship. That’s not much different from the way employment has
worked throughout the ages. We’re talking about bringing people in from
outside and involving them in this broadly creative, collaborative
process.”

InnoCentive’s solvers are not who you’d expect. Many are hobbyists
working from their proverbial garage, like the University of Dallas
undergrad who came up with a chemical to use in art restoration, or the
North Carolina, patent lawyer who devised a novel way to mix large
batches of chemical compounds. Or in Melcarek’s case, a mildly
eccentric electrical engineer whose lab doubles as a music studio. Yet
Melcarek solved a problem that had stumped the in-house researchers at
Colgate-Palmolive. The giant packaged goods company needed a way to
inject fluoride powder into a toothpaste tube without it dispersing
into the surrounding air. Melcarek knew he had a solution by the time
he’d finished reading the challenge: Impart an electric charge to the
powder while grounding the tube. The positively charged fluoride
particles would be attracted to the tube without any significant
dispersion.

“It was really a very simple solution,” says Melcarek. Why hadn’t
Colgate thought of it? “They’re probably test tube guys without any
training in physics.” Melcarek earned $25,000 for his efforts. Paying
Colgate-Palmolive’s R&D staff to produce the same solution could
have cost several times that amount – if they even solved it at all.
Melcarek says he was elated to win. “These are rocket-science
challenges,” he says. “It really reinforced my confidence in what I can
do.”

Melcarek, who favors thick sweaters and a floppy fishing hat, has
charted an unconventional course through the sciences. He spent four
years earning his master’s degree at the world-class particle
accelerator in Vancouver, British Columbia, but decided against
pursuing a PhD. “I had an offer from the private sector,” he says, then
pauses. “I really needed the money.” A succession of “unsatisfying”
engineering jobs followed, none of which fully exploited Melcarek’s
scientific training or his need to tinker. “I’m not at my best in a
9-to-5 environment,” he says. Working sporadically, he has designed
products like heating vents and industrial spray-painting robots. Not
every quick and curious intellect can land a plum research post at a
university or privately funded lab. Some must make HVAC systems.

InnoCentive has been a ticket out of this scientific backwater for
Melcarek. For the past three years, he has logged onto the network’s
Web site a few times a week to look at new challenges. Until recently
these had been categorized as either chemistry or biology problems.
Melcarek has formal training in neither discipline, but he quickly
realized this didn’t hinder him. “I saw that a lot of the chemistry
challenges could be solved using electromechanical processes I was
familiar with from particle physics,” he says. Besides the fluoride
injection challenge, Melcarek also devised a successful method for
purifying silicone-based solvents. That challenge paid $10,000.
Melcarek has since gone on to win five additional InnoCentive
challenges. “Not bad for a few weeks’ work,” he says with a chuckle.

Melcarek has discovered something of a winning formula: Find chemistry
or biology problems that he can crack using his background in physics
and electrical engineering. In 2007 InnoCentive launched a category for
engineering challenges, but Melcarek doesn’t bother with it. All seven
of the problems Melcarek has solved were in other fields.

This says a little something about Melcarek (he’s a man who likes to
work off hunches), but it says a lot more about InnoCentive. When
Lakhani dug into InnoCentive’s data, he discovered that Melcarek wasn’t
the exception, he was the rule—the scientists most likely to solve a
problem were the ones you’d least expect to be capable of solving it.
“We actually found the odds of a solver’s success increased in fields
in which they had no formal expertise,” Lakhani says. The further the
problem was from their specialized knowledge, the more likely it was to
be solved. “Think of the problem as a flower. Except the goal is to
attract not only the most insects, but the most diverse group of
insects.”

And Lakhani’s paper contained an even more interesting gem: A full 75
percent of successful solvers already knew the solution to the problem.
The solutions to the problems in the study—many of which, recall, had
stumped the best corporate scientists in the world after years of
effort—didn’t require a breakthrough, or additional brainpower, or a
more talented scientist’s attention; they just needed a diverse enough
set of minds to have a go at them. It would seem to be evidence that
Hayek was right: Civilization’s progress lies not in acquiring new
knowledge, but in aggregating and utilizing the knowledge we already
have. When I asked Melcarek how long he spent solving InnoCentive
problems, his answer was telling. “If I don’t know what to do after 30
minutes of brainstorming, I give up.”

Lakhani’s findings may be news to people in business and science,
fields in which the vogue for specialization has reigned for many
decades. But they dovetail neatly with decades of research in economic
sociology, echoing a principle sociologists call “the strength of weak
ties.”

In 1972 a young sociologist at Harvard named Mark Granovetter crossed
the Charles River and asked some 282 professional, technical and
managerial workers in Newton, Massachusetts how they’d found their
jobs. Not surprisingly, many of Granovetter’s respondents told him
they’d used personal contacts, confirmation of the old saw: “It’s not
what you know, it’s who you know.” Granovetter, however, dug a little
deeper. What kind of personal contact, he wanted to know. Spouse?
Brother? Best friend? The majority, it turned out, answered no, no and
no. Only 16.7 percent found their job through a close acquaintance,
while the rest had secured their position through someone they barely
knew. The people who were most helpful were the friends of friends. The
people we know well know all the same things—the same eligible singles,
the same job openings and the same available apartments—that we know.
What Granovetter discovered is that it’s not, in fact, who we know that
gets us ahead in life, it’s who we don’t know well.

The strength of weak ties doesn’t just apply to getting jobs. “There’s
a strong tendency in human networks to homophily, which means that
birds of a feather stick together,” says Lakhani. “And so even when a
company chooses to look to external sources for a solution to a
problem, they’ll rely on people and companies and labs they already
know well, so they run into the same local search biases that are
present in internal problem solving.” In this light, it no longer seems
so mysterious that the leading chemists at a company like P&G might
fail to solve a problem that Ed Melcarek can knock off over a couple
glasses of brandy.

The key to making it work is to broadcast the problem using a massive
network like InnoCentive’s. Or to return to Lakhani’s metaphor, to make
your flower attractive to as many insects as possible. That’s easier
said than done. “Firms aren’t set up to broadcast their inner problems
to outsiders. Traditional corporate culture is geared to limit outsider
access to insider information, not increase it. And what could be more
insidery than some problem they’re really stumped on?” Of course, this
only makes for greater opportunities for companies willing to swim
against the tide.

If an uneducated cabinetmaker can solve one of the most perplexing
challenges of his day, if an electrical engineer can solve some of the
thorniest chemistry problems encountered by Fortune 500 companies, then
maybe MATLAB’s Ned Gulley isn’t off base in suggesting that the
collective brain might one day cure cancer. It’s not as remote a
prospect as it sounds. Taking a page from the distributed computing
project, SETI@home, Stanford University’s chemistry department created
Folding@home, which uses the excess capacity of hundreds of thousands
of individual PCs to simulate protein folding—the process in which
proteins combine to form biological molecules—a crucial step in
understanding diseases like cystic fibrosis, Alzheimer’s disease and
cancer.

It’s a short leap to go from tapping the excess capacity of thousands
of computers to tapping the excess capacity of thousands of brains.
This gets to the heart of F.A. Hayek’s proposition: the answers to our
present day’s equivalent of the longitude problem lie not in the
acquisition of more knowledge, but simply in gathering up all the
knowledge that is already spread out among individuals throughout the
world. In fact, it’s already occurring. What happens when the
Billion—the approximate size of the crowd, which is to say, the number
of people connected to the Internet—becomes the Three Billion. What
feats of cognition might all these brains, working together, produce?

The possibility of crowdsourcing difficult problems has even been
broached in that most unlikely crucible of innovation—the federal
government. In October 2007, Senator Bernie Sanders, an independent
from Vermont, introduced a bill that would replace the drug monopolies
given to pharmaceutical companies by the patent department with a
system of cash prizes. The bill calls for the government to create a
$80 billion fund, which would then be awarded for narrowly targeted
medical objectives, such as developing part of a cure for malaria. At
present, pharmaceutical companies have little incentive to conduct
research into such life-saving treatments. Drug firms like Merck make
an easy target for their seeming callous disregard for killers like
malaria, but the fact is that research and development of such drugs is
incredibly expensive, and the readiest customers are also the poorest,
meaning the pharmaceutical companies would have a very difficult time
earning their money back on a malaria drug. Sanders’ bill would address
this issue by essentially guaranteeing compensation to any individual
or company who successfully develops such a drug.

Sanders isn’t alone in conceiving of problem-solving crowdsourcing as a
potential alternative to traditional R&D. Awarding prizes for
breakthroughs in medical science have been proposed by former US
Senator John Edwards. On the other side of the aisle, Newt Gingrich has
proposed a similar system for alleviating government spending. As
William Saleton wrote in Slate in October of 2007, Gingrich suggests
that “instead of giving $1 billion to a federal agency to deal with a
problem … offer the money as a prize to the first company that solves
it. As the conversation proceeds, Gingrich throws money at one
challenge after another. Hydrogen fuel? Dangle a 10-figure prize.”

Comments

The interesting question that all this evokes is "Does crowdsourcing scale?" You argue well for the fact that by spreading out a problem and incentivizing, one can get interesting new answers. But does it scale. Yes, in the case of Linux coding it clearly did so, and the crowd organized itself in interesting ways. But in most of the examples that one puts forward, it is the case of either single designs or single inventions, often then improved by a more traditional R&D-unit. When one guesses that the problem of cancer could be solved through crowdsourcing, one ignores much of the tricky combinatorics that lies behind more complicated systemic innovations. Yes, with enough people behind it, we might be able to map genomic sequences over and over again until we hit upon something, but can all this be automated? Is there no need for a more centralized oversight?

When my laptop runs the SETI@home, it just means that I lend a few cycles, dumb cycles, and that these will be filtered by an algorithm created by the people behind SETI@home, and if I by chance come upon something, the people from S@h will look at it and decide if they've found something. In a sense this would be a very "pure" utilization of resources, effectively doing something with a resource that otherwise would lie fallow.

The logic of crowdsourcing says something similar, but forgets one thing. Those who do not succeed to see their work prominently displayed will, unlike my laptop, care about the fact that they've spent time that didn't really help anyone (least of all themselves).

Scaling crowdsourcing would somehow be able to muster both the greater systemic logic to oversee a project, and at the same time be able to overcome the problem of what happens to the underutilized (and not necessarily replicating) resources. As an example, just look at the number of open source projects that either fail or never get off the ground at all. Yes, I know the counter-argument is that there are enough "cycles" to go around, but I have yet to see any solid evidence for this...

“The current R&D model is broken.” P&G is one of InnoCentive’s earliest and best customers, but the company works with other crowdsourcing networks as well.”

I wouldn’t have abbreviated Procter & Gamble immediately following R&D.

“Not every quick and curious intellect can land a plum research post at a university or privately funded lab. Some must make HVAC systems.”

Why did you choose HVAC systems as the lowest common denominator against a plum research post at a university or privately funded lab?

“Fortune 500 companies, then maybe MATLAB’s Ned Gulley isn’t off base in suggesting that the collective brain might one day cure cancer.”

Calling it a collective brain Jeff is just spin That is quite a stretch from Collective Intelligence
“But they dovetail neatly with decades of research in economic sociology, echoing a principle sociologists call “the strength of weak ties.”

Very interesting concept, the fact that it is important to recognize the difference between a nod tie, weak tie and an absent one gives it some context Jeff.

Just a quick note to future commenters: Alan's approach here is spot on, in that he quotes the relevant passage he's responding to, then writes his comment below. The idea is to create end-note symbols that will correspond to the appropriate parts of the appendix. If you reply generally to the excerpt, it makes this task more difficult (though not impossible.) Make sense?

First, thanks for sharing all this on your blog! I'll start with a tiny copy-editing quibble. In this passage:

“I read that and thought, ‘Huh. Kind of like open source. Someone poses a problem and all sorts of random, strange people show up and say I’ve got an answer for you, and it’s never the one you’d anticipate.”

You need an end-quote for the thought beginning with 'Huh.'

Now for the deeper thought:

"The longitude prize constitutes the earliest known example of crowdcasting—broadcasting a problem to the widest possible audience in the blind hope that someone, somewhere—maybe even a Yorkshire cabinetmaker—will come up with a solution."

I got here through a little crowdcasting of your own -- I saw a post on Tish Grier's blog indicating you needed a little more involvement in this blog. That suggests to me that crowdsourcing *can* scale, but that it takes a lot of work to make it do so. It sounds like you'd like the editing process of your book on crowdsourcing to be crowdsourced itself -- a laudable goal -- but it's not as easy as it sounds, is it? Good crowdsourcing needs to achieve critical mass somehow, through word-of-mouth (word-of-blog?) or some other mechanism. In short, good old-fashioned publicity. And so in its own way, the new is old.

This is just my random riff on a quick read of this chapter. I may have more to say after I read more of the book. I just got here, so please forgive me if other commenters have already said much the same thing.

This is just my random riff on a quick read of this chapter. I may have more to say after I read more of the book. I just got here, so please forgive me if other commenters have already said much the same thing.

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